Real-time Boundary Research Articles

Superstable homogeneous lipiodol-ICG formulation: initial feasibility and first-in-human clinical application for ruptured hepatocellular carcinoma.

The most common treatment of spontaneous tumor rupture hemorrhage (STRH) is transcatheter arterial embolization (TAE) followed by liver resection, and surgical navigation using near-infrared fluorescence is effective method for detecting hidden lesions and ill-defined tumor boundaries. However, due to the blockage of the tumor-supplying artery after effective TAE treatment, it is difficult to deliver sufficient fluorescent probes to the tumor region. In this study, we report on the successful application of superstable homogeneous intermixed formulation technology (SHIFT) in precise conversion hepatectomy for ruptured hepatocellular carcinoma (HCC). A homogeneous lipiodol-ICG formulation obtained by SHIFT (SHIFT-ICG) was developed for clinical practice for STRH. A ruptured HCC patient received the combined protocol for embolization and fluorescence surgical navigation and exhibited excellent hemostatic effect. Lipiodol and ICG were both effectively deposited in the primary lesion, including a small metastatic lesion. In follow-up laparoscopic hepatectomy, SHIFT-ICG could clearly and precisely image the full tumor regions and boundaries in real time, and even indistinguishable satellite lesions still expressed a remarkable fluorescence intensity. In conclusion, the simple and green SHIFT-ICG formulation can be effectively used in emergency embolization hemostasis and later precise fluorescence navigation hepatectomy in patients with ruptured HCC bleeding and has high clinical application value.

Towards a full automation of land consolidation projects: Fast land partitioning algorithm using the land value map

One of the key stages of land consolidation is land reallocation, over the course of which the land of individual owners is pre-allocated to the blocks into which the project area is divided. The key to such an assignment is a set of adopted criteria, the most important of which are the effects of interviewing landowners. The problem of land partitioning is solved either as an optimisation issue in view of the assumed criteria, or as a technical problem related to the automation of the division of a block into new plots with an accuracy sufficient to create the consolidation project documentation and the accuracy requirements of cadastral databases. The article presents an algorithm of an analytical way of dividing a block of any differentiation of the land's value and any shape of the block itself, according to the adopted direction of the course of the new borders. The algorithm may be applied in cases, in which the plot boundaries are parallel to each other and run across the entire block. The speed of the algorithm enables dynamic determination of the plot boundaries in real time.

Singular Perturbation Method Applied for BVP, IVP and Optimal Control to One Parameter Armature Controlled DC Servo Motor

DC servo motor discrete model of one-parameter Singular Perturbation Method (SPM) is enlarged showing zero-order, first-order and second-order approximations. In this paper, a one parameter SPM based two time scale model is considered for evaluation. Now by applying this SPM a real time Boundary Value Problems (BVP), Initial Value Problem (IVP) and Optimal Control Problem (OCP) are premeditated. Such evaluated SPM have a boundary layer correction (BLC) solution and an outer series solution. To improve degenerate solution and to recover initial and boundary conditions a BLC solution of SPM is used. The DC servo-motor control model of second order approximation is carried out for BVP, IVP and OCP. The results thus obtained are presented in comparison to the precise solution. The efficacy of the present model is evaluated in MATLAB environment.

Energy-dependent Boundaries of Earth's Radiation Belt Electron Slot Region

Abstract The variations in radiation belt boundaries reflect competition between acceleration and loss physical processes of energetic electrons, which is an important issue for radiation belts of planets with an internal magnetic field (e.g., Earth, Jupiter, and Saturn). Based on high-quality measurements from Van Allen Probes spanning the years 2014–2018, we develop an empirical model of the energy-dependent boundaries of Earth's electron radiation belt slot region, showing that the lower boundary follows a logarithmic function of the electron energy while the upper boundary is controlled by two competing energy-dependent processes, namely compression and recovery. The compression process relates linearly to a 15 hr averaged Kp index, while the recovery process is found to be approximately proportional to time. Detailed data-model comparisons demonstrate that our model, using only the Kp index and time epoch as inputs, reconstructs the slot region boundaries in real time for 200 keV to 2 MeV electrons under varying geomagnetic conditions. Such a data-driven empirical model is prerequisite to understanding the dynamic changes of the slot region in response to both solar and geomagnetic activities. The model can be readily incorporated into future global simulations of radiation belt electron dynamics in Earth's inner magnetosphere and provide new insights into the study of Saturn's and Jupiter's radiation belt variability.

A Real-Time Curb Detection Method for Vehicle by Using a 3D-LiDAR Sensor

<div class="section abstract"><div class="htmlview paragraph">Effectively detecting road boundaries in real time is critical to the applications of autonomous vehicles, such as vehicle localization, path planning and environmental understanding. To precisely extract the road boundaries from the 3D-LiDAR data, a dedicated algorithm consisting of four steps is proposed in this paper. The steps are as follows: Firstly, the 3D-LiDAR data is pre-processed by employing the RANSAC method, the ground points are quickly separated from the original 3D-LiDAR point cloud to reduce the disturbance from the obstacles on the road, this greatly decreases the size of the point cloud to be processed. Secondly, based on the principle of 3D-LiDAR scanning, the ground points are divided into scan layers. And the road boundary points of each scan layer are detected by using three spatial features based on sliding window. Thirdly, based on the improved beam model, the road type (straight road or curved road) where the vehicle is located is predicted, and then the edge points are subdivided into different areas by the road type. Finally, we use the distance filtering and RANSAC filtering to filter out false road boundary points caused by obstacles and obtain accurate road boundaries. Compared to other methods, we can effectively reduce the wrong classification of road edge points caused by obstacles by using the improved beam model. And the false points caused by obstacles are effectively reduced by using distance filtering and RANSAC filtering. The performance of the proposed method is verified through experiments with a vehicle driving on campus roads and extensive tests with the KITTI data set the experimental results demonstrate the accuracy and robustness of the proposed method.</div></div>

The Ontology of Globalization and Sensemaking of Industrial Work in the Age of Digital Electronics

Abstract Today industrial production is performed across national boundaries in real time with great accuracy and precision using digital information communication technologies. Manufacturing in one location is possible as it receives digital signals and messages transmissions from remote activities across borders. But who are these magicians behind the curtain? They are the highly skilled and educated knowledge workers of the global, blue-collar, working class. A generation ago working in industrial settings we would have likely shared close physical proximity as well as a common language and culture. Today we share the interconnectedness of our global village across national, cultural, and linguistic boundaries.

Real-Time Hierarchical Supervoxel Segmentation via a Minimum Spanning Tree.

Supervoxel segmentation algorithm has been applied as a preprocessing step for many vision tasks. However, existing supervoxel segmentation algorithms cannot generate hierarchical supervoxel segmentation well preserving the spatiotemporal boundaries in real time, which prevents the downstream applications from accurate and efficient processing. In this paper, we propose a real-time hierarchical supervoxel segmentation algorithm based on the minimum spanning tree (MST), which achieves state-of-the-art accuracy meanwhile at least 11× faster than existing methods. In particular, we present a dynamic graph updating operation into the iterative construction process of the MST, which can geometrically decrease the numbers of vertices and edges. In this way, the proposed method is able to generate arbitrary scales of supervoxels on the fly. We prove the efficiency of our algorithm that can produce hierarchical supervoxels in the time complexity of O(n) , where n denotes the number of voxels in the input video. Quantitative and qualitative evaluations on public benchmarks demonstrate that our proposed algorithm significantly outperforms the state-of-the-art algorithms in terms of supervoxel segmentation accuracy and computational efficiency. Furthermore, we demonstrate the effectiveness of the proposed method on a downstream application of video object segmentation.

A 3D LiDAR Data-Based Dedicated Road Boundary Detection Algorithm for Autonomous Vehicles

Effectively detecting road boundaries in real time is critical to the applications of autonomous vehicles, such as vehicle localization, path planning, and environmental understanding. To precisely extract the irregular road boundaries or those blocked by obstructions on the road from the 3D LiDAR data, a dedicated algorithm consisting of four steps is proposed in this paper. The steps are as follows. First, the 3D LiDAR data is pre-processed, employing the vehicle position and attitude information, and many noise points are deleted. Second, the ground points are quickly separated from the pre-processed point cloud data to reduce the disturbance from the obstacles on the road; this greatly decreases the size of the points cloud to be processed. Third, the candidate points of the road boundaries are searched along the predicted trajectory of the autonomous vehicle and filtered using the unique features of the boundary points. Last, a spline fit model is applied to smoothen the road boundaries. An experiment to test the performance of the proposed algorithm was conducted on the “Xinda” autonomous vehicle under various road scenarios. The experimental results show that the average accuracy of the proposed algorithm exceeds 93%, and its average processing time is approximately 36.5 ms/frame, which outperforms most of the state-of-the-art methods. This indicates that the proposed algorithm can robustly extract the road boundary in real time even if there are many obstacles on the road. This algorithm has been tested on “Xinda” autonomous vehicle for over 1000 kilometers, and its performance was always stable.

Dynamics of Symmetry-Breaking Stacking Boundaries in Bilayer MoS2

Crystal symmetry of two-dimensional (2D) materials plays an important role in their electronic and optical properties. Engineering symmetry in 2D materials has recently emerged as a promising way to achieve novel properties and functions. The noncentrosymmetric structure of monolayer transition metal dichalcogenides (TMDCs), such as molybdenum disulfide (MoS2), has allowed for valley control via circularly polarized optical excitation. In bilayer TMDCs, inversion symmetry can be controlled by varying the stacking sequence, thus providing a pathway to engineer valley selectivity. Here, we report the in situ integration of AA' and AB stacked bilayer MoS2 with different inversion symmetries by creating atomically sharp stacking boundaries between the differently stacked domains, via thermal stimulation and electron irradiation, inside an atomic-resolution scanning transmission electron microscopy. The setup enables us to track the formation and atomic motion of the stacking boundaries in real time and with ultrahigh resolution which enables in-depth analysis on the atomic structure at the boundaries. In conjunction with density functional theory calculations, we establish the dynamics of the boundary nucleation and expansion and further identify metallic boundary states. Our approach provides a means to synthesize domain boundaries with intriguing transport properties and opens up a new avenue for controlling valleytronics in nanoscale domains via real-time patterning of domains with different symmetry properties.

Identification of critical transmission limits in injection impedance plane

In this paper, equations are derived that describe the mapping of critical boundaries and characteristic curves from the three dimensional PQV-surface into the two-dimensional injection impedance plane (load impedance plane for both positive and negative resistance). The expressions derived for the critical and characteristic curves in the impedance plane form the basis for a new phasor measurement based situational awareness method, which uses the results in this paper to identify critical operational boundaries in real time and to visualize the system operating conditions in an informative way. The situational awareness method will be described in a later paper, where this paper focuses on the derivations of some system characteristics in the injection (or load) impedance plane. The critical curves from the PQV-surface that are mapped into the impedance plane are the ones representing the conditions where the partial derivatives of the variables P, Q and V in respect to each other become zero. In addition to the mapping of the critical curves, some characteristic curves are mapped as well. These include the mapping of the curves of constant P, Q, V and δ from the PQV-surface into the impedance plane. All of the mapped critical and characteristic curves appear as circles in the injection impedance plane.

Transport and biotransformation of organic carbon and nitrate compounds in unsaturated soil conditions

The lack of drinking water was one of the hot environmental issues that focused on the contaminants released from the failure of sanitary systems. Organic carbon and nitrate compounds were concerned since they represented a potential risk to human health and environment. Mathematical modelling was an effective tool for understanding and estimating the fate and transport of contaminants. An organic carbon and nitrate compounds transport model was developed using the mass balance concept. Richards and multiplicative Monod equations supported the estimating of advection-dispersion transport and biodegradation processes, respectively. The numerical solutions were obtained using the MATLAB programme. The model capability was evaluated using pilot scale experimental data. The depth-averaged time series of pressure head and contaminants concentration profiles were measured several times a week during 91 days. Simulations were found to provide reasonable agreement with the observed data. The aerobic biodegradation zone was observed within 15 cm depth of soil column. Even though the column was operated for 91 days, soil microbes were enough to retard these contaminants. This confirmed that the developed model could be applied to simulate the transport of the contaminants under real time boundary conditions.

Identification of the ionospheric footprint of magnetospheric boundaries using SuperDARN coherent HF radars

Several studies of SuperDARN radar data have revealed a systematic dependence of the Doppler backscatter versus latitude and magnetic local time. In particular, the Doppler spectral width is known to increase at the vicinity of the ionospheric footprint of the cusp, and in a region that shapes like the poleward boundary of the auroral oval. Following earlier work, we make use of a large radar database consisting of a set of key parameters that characterize Doppler backscatter, and a multivariate statistical method, to reveal a strong connection between specific geophysical regions and their backscatter properties. This opens the interesting perspective of monitoring magnetospheric boundaries in real time.

Interobserver reproducibility of quantitative cartilage measurements: comparison of B-spline snakes and manual segmentation

The objective of this work was to develop a segmentation technique for thickness measurements of the articular cartilage in MR images and to assess the interobserver reproducibility of the method in comparison with manual segmentation. The algorithm is based on a B-spline snakes approach and is able to delineate the cartilage boundaries in real time and with minimal user interaction. The interobserver reproducibility of the method, ranging from 3.3 to 13.6% for various section orientations and joint surfaces, proved to be significantly superior to manual segmentation.

AN INPUT ESTIMATION APPROACH TO ON-LINE TWO-DIMENSIONAL INVERSE HEAT CONDUCTION PROBLEMS

Abstract An on-line methodology to solve two-dimensional inverse heat conduction problems (IHCP) is presented. A new input estimation approach based on the Kalman filtering technique is developed to estimate the two separate unknown heat flux inputs on the two boundaries in real time. A recursive relation between the observed value of the residual sequence with unknown heat flux and the theoretical residual sequence of the Kalman filter that assumes known heat flux is formulated. A real-time least-squares algorithm is derived that uses the residual innovation sequence to compute the magnitude of heat flux. This recursive approach facilitates practical implementation, and its capabilities are demonstrated in several typical cases with discontinuous and time-varying heat flux inputs.